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Phone

+886 2 8797 8337

HQ

12F-2, No.408, Ruiguang Rd., Neihu Dist., Taipei City 11492, Taiwan

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Center of Innovative Incubator R819, No. 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan

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The Industrialization of AI

Skymizer’s system software solutions enable AI-on-Chip design houses to automate AI application development,
improve system performance, and optimize inference accuracy.
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Our Key Values

Automate Application Development

Enable AI SoC to be easily adopted in frequently evolved applications by automatically compiling AI algorithms into chip’s machine code.

Analyze System Bottlenecks

Leverage virtual platforms to conduct Performance-Guided Optimizations (PGO) to improve speed and reduce memory requirements by utilizing all available computing/memory resources in the complex heterogeneous multicore systems.

Enhance Accuracy and Performance through Hardware/Software Co-optimization

Align software development at a much earlier stage during SoC architecture exploration stage. Provide architecture-aware calibrations to maintain precision even in Int8 mode.

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Products

ONNC

Commercial
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ONNC

Commercial
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ONNC compiler is a bundle of C++ libraries and tools to boost your development of compiler for deep learning accelerators (DLAs). ONNC compiler targets on diverse SoC architectures from a simply single core system to a heterogeneous system with multi-level memory hierarchy and bus connection.

Forest
Runtime

Commerical
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Forest
Runtime

Commerical
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Forest Runtime executes compiled neural network models on the hardware platform of your choice. It provides common C++ APIs with C and Python bindings for various AI application doing inference. Forest Runtime is '''retargetable'''. It has modular architecture and we've ported it on diverse hardware platforms, including ''datacenter'', ''mobile'' and ''TinyML''.

Calibrator

Commerical
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Calibrator

Commerical
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ONNC Calibrator leverages hardware architecture information to keep AI System-on-Chips in high precision through the post-training quantization (PTQ) technique. The key indicator to validate a quantization technique is its precision drop.